Galaxy IPython is a visualization plugin which should enable Galaxy users with coding skills to easily process their data in the most flexible way. With this plugin, it is possible to analyse and post-process data without downloading datasets or entire histories. One of our aims was to make Galaxy more attractive and accessible to bioinformaticians and programmers, and we hope that this project will build some bridges.

Screencast:

Disclaimer: Even though the Ipython notebooks can be stored and reused, this plugin will break the Galaxy philosophy of reproducibility, I feel personally bad about that, but I also think it is a great opportunity to get more bioinformaticians into Galaxy, and to get Galaxy used more often as a teaching resource. By being able to teach not only about workflows but also about data analysis tasks often necessary with Bioinformatics, Galaxy will be significantly more useful in teaching environments.

Keep in mind to write a nice Tool Shed Tool if you catch yourself using IPython in Galaxy to often for the same task.

A few features we have up and running:
Use IPython directly in the main window or in the Scratchbook
Completely encapsulated IPython environment with matplotlib, biopython, pandas and friends already installed.
IPython runs completely self-contained within a docker container, separate from your Galaxy data
Easy access to datasets from your current history via pre-defined IPython functions
Manipulate and plot data as you like and export your new files back into your Galaxy history
Save IPython Notebooks across analysis sessions in your Galaxy history with the click of a button.
View saved IPython Notebooks directly in HTML format, or re-open them to continue your analysis.
Self-closing and self-cleaning IPython docker container
Notebooks are secure, only accessible to the intended user